CN103336052B - A kind of indoor relative humidity on-line monitoring system and humidity computing method - Google Patents

Abstract

The invention discloses a kind of indoor relative humidity on-line monitoring system and the humidity computing method in environmental index monitoring field.The metope that indoor are relative is installed the sound wave measuring system of dynamic loudspeaker, microphone, temperature sensor and pressure transducer composition respectively, dynamic loudspeaker is sounded signal, detected by the microphone of homonymy, then voice signal is received by the microphone on the relative body of wall in indoor, voice signal will be received and be transformed into voltage signal, digital signal is changed to by entering data collecting card after cable input signal conditioning device, draw acoustic transit time by delay algorithm meter again, calculate the velocity of propagation of sound wave in indoor.Pressure transducer and temperature sensor probe simultaneously by being positioned at two bodies of wall carry out the temperature and pressure of detecting chamber.Indoor relative humidity is calculated finally by main control computer.The present invention can be accurately real-time the medial humidity of the whole indoor of measurement, can the change of real time record indoor humidity.

Description

A kind of indoor relative humidity on-line monitoring system and humidity computing method

Technical field

The invention belongs to environmental index monitoring field, particularly relate to a kind of indoor relative humidity on-line monitoring system and humidity computing method.

Background technology

At present, the measuring method of indoor relative humidity is a lot, generally mainly contains following several:

1. pair platen press, dual-temperature process: the method is based on thermodynamics P, V, T equilibrium principle, and equilibration time is longer, shunting is the accurate mixing based on absolute moisture and absolute dry air.It is quite accurate that these equipment can do, but because of equipment complicated, expensive, operate time-consuming taking a lot of work, mainly as the use of standard metering.

2. saturated salt method: modal method in moisture measurement, simple.But saturated salt method is very tight to the balance requirement of gas-liquid two-phase, higher to the stability requirement of environment temperature, use to require to wait and go balance for a long time, low four degree of points require longer.Especially indoor humidity and bottle humidity value difference value larger time, each unlatching all will balance 6 ~ 8 hours.

3. dew point method: the method measures temperature when soft air reaches capacity, and be thermodynamic (al) direct result, accuracy is high, and measurement range is wide.But expensive with the chilled-mirror type dew point instrument of a modern light-principle, normal and standard humidity generator supports the use.And when cooling surface occurring the moment of dewdrop, needing chart surface temperature immediately, but generally not easily surveying standard, and easily causing larger measuring error.

4. measurement with wet: the method is a kind of indirect method, and it converses humidity value with wet and dry bulb equation, and equation of n th order n requires that the custom near wet bulb must reach more than 2.5m/s.Measuring error is larger.

5. moisture absorption method: mainly measure with lithium chloride electric resistance humidity sensor, make, but its range is narrower according to resistance variation characteristic after the moisture-absorption characteristics of lithium chloride and moisture absorption, and environment temperature is comparatively large on output impact, carry out temperature compensation.Maximum operation (service) temperature is 55 DEG C, and when being greater than 55 DEG C, lithium chloride solution easily evaporates.In order to avoid lithium chloride solution origination point solution, motor two termination be alternating current.And environment for use requires to keep air cleaner, without dust, fiber etc.Service condition is comparatively harsh.

Above various methods require that the time of measuring is longer, can not measuring chamber humidity in time, and the mainly indoor humidity locally measured, to the medial humidity of entirety measure less.

Summary of the invention

Precision is there is not high for the humidity detector that the current indoor mentioned in background technology are conventional, measurement range is less, cannot real time on-line monitoring be realized, the problem of remote monitoring cannot be realized, the present invention proposes a kind of indoor relative humidity on-line monitoring system and humidity computing method.

A kind of indoor relative humidity on-line monitoring system, it is characterized in that, described system comprises two acoustic measurement devices, signal conditioner, power amplifier, data collecting card, sound card and main control computers; Described acoustic measurement device comprises dynamic loudspeaker, microphone, temperature sensor, pressure transducer and terminal box;

Wherein, described power amplifier, microphone, temperature sensor and pressure transducer are connected with the input end of terminal box respectively; The output terminal of described terminal box is connected with described signal conditioner and dynamic loudspeaker respectively; Described signal conditioner, data collecting card are connected in turn with main control computer; Described power amplifier, sound card are connected in turn with main control computer;

Described dynamic loudspeaker is used for signal of sounding; Described microphone is used for voice signal to be converted to voltage signal; Described temperature sensor is for detecting indoor temperature; Described pressure transducer is for detecting room pressure; Described signal conditioner is used for carrying out signal condition to the received signal; Described data collecting card is for gathering for the signal collected being converted to digital signal and sending to main control computer; The sound that described power amplifier is used for sound card produces amplifies.

Described two acoustic measurement devices are installed on the relative position on the indoor same cross section of body of wall relatively; One of them acoustic measurement device is as flexible piezoelectric sound-generating devices, and another acoustic measurement device is as sound receiver.

Described microphone is connected with described signal conditioner by cable.

A kind of indoor relative humidity computing method, it is characterized in that, described method specifically comprises the following steps:

Step 1: according to water capacity formula gentle/liquid two-phase in the expression formula of the velocity of sound obtain the computing formula of indoor relative humidity;

Step 2: employing time delay algorithm draws the acoustic transit time τ between two microphones;

Step 3: because the distance between two microphones is fixed and known, calculate the acoustic wave propagation velocity c of sound wave between two microphones;

Step 4: the acoustic wave propagation velocity c that step 3 is obtained, the temperature T that the pressure P recorded according to pressure transducer and temperature sensor record, and by drawing indoor atmospheric density ρ in main control computer ₁, water vapour density p ₂and pressure P _ssubstitute in the coefficient expressions of the computing formula of indoor relative humidity, thus draw design factor A, B and the C in indoor relative humidity formula, and then go out indoor relative humidity by indoor relative humidity formulae discovery.

In described step 1, according to water capacity formula gentle/liquid two-phase in the expression formula of the velocity of sound detailed process that obtains the computing formula of indoor relative humidity be:

$c=c_1{\left\{\frac{[{\mathrm{\α\ρ}}_1+(1-\mathrm{\α}+C_R){\mathrm{\ρ}}_2]{\mathrm{\ρ}}_1}{(1-\mathrm{\α}){\mathrm{\ρ}}_2(1+C_R-\mathrm{\α}{C}_R){\mathrm{\ρ}}_1+\mathrm{\α}{C}_R{\mathrm{\ρ}}_2}\right\}}^{\frac{1}{2}}---\left(2\right)$

Wherein, c is sound velocity of wave propagation in medium, unit: meter per second; ρ ₁for the density of air, unit: kilograms per cubic meter; ρ ₂for the density of water vapor, kilograms per cubic meter; C _rfor mass coefficient; P _sfor equality of temperature is with steam-laden partial pressure in the saturated wet steam of pressure, unit: Pascal; P is the pressure that pressure transducer records; T is the temperature that temperature sensor records, unit: degree Celsius; for indoor relative humidity; wherein γ is the adiabatic exponent of gas; R is gas molar quality;

For certain tested object, the air of its indoor and the density of water vapor can be tried to achieve by pressure and temperature.For indoor, because air flow property is less, so can C be got _r→ ∞, γ are constant; Therefore when temperature and pressure is known, sound velocity of wave propagation depends on indoor relative humidity, thus simultaneous (1) and (2) draw the computing formula about indoor relative humidity:

Wherein, coefficient A, B, C is the design factor of relative humidity; The expression formula of coefficient is:

$A=155500P_s^2{\mathrm{\ρ}}_{1}c({\mathrm{\ρ}}_1{\mathrm{\ρ}}_2{c}^2+{\mathrm{\ρ}}_2{C}_R{c}^2-{\mathrm{\ρ}}_1^2{c}_1^2-{\mathrm{\ρ}}_1{\mathrm{\ρ}}_2{c}_1^2-2{\mathrm{\ρ}}_1{{\mathrm{\ρ}}_2{C}_{R}c}_1^2)$

$-25000{\mathrm{\ρ}}_1^3{\mathrm{\ρ}}_2{P}_s^2(c^2+c^2{C}_R-c_1^2-C_R{c}_1^2)$

$+96721P_s^2{c}^2(-{\mathrm{\ρ}}_2{C}_R{c}^2+{\mathrm{\ρ}}_1^2{c}_1^2+{\mathrm{\ρ}}_1{\mathrm{\ρ}}_2{C}_R{c}_1^2);$

$B=50000{\mathrm{\ρ}}_1^3{\mathrm{\ρ}}_2{P}_{s}P(c+C_R{c}^2-c_1^2-C_R{c}_1^2)+155500{\mathrm{\ρ}}_1{P}_s\mathrm{Pc}(-{\mathrm{\ρ}}_1{\mathrm{\ρ}}_2{c}^2$

$-{\mathrm{\ρ}}_2{C}_R{c}^2+{\mathrm{\ρ}}_1^2{c}_1^2+2{\mathrm{\ρ}}_1{\mathrm{\ρ}}_2{C}_R{C}_1^2);$

$C=250000{\mathrm{\ρ}}_1^3{\mathrm{\ρ}}_2{P}^2(c_1^2-C_R{c}^2-{\mathrm{\ρ}}_1{c}^2+{\mathrm{\ρ}}_1{C}_R{c}_1^2);$

Wherein, c is sound velocity of wave propagation in medium, unit: meter per second; ρ ₁for the density of air, unit: kilograms per cubic meter; ρ ₂for the density of water vapor, kilograms per cubic meter; C _rfor mass coefficient; P _sfor equality of temperature is with steam-laden partial pressure in the saturated wet steam of pressure, unit: Pascal; P is the pressure that pressure transducer records; T is the temperature recorded by temperature sensor, unit: degree Celsius; for indoor relative humidity; wherein γ is the adiabatic exponent of gas; R is gas molar quality;

The process of the acoustic transit time τ that described employing time delay algorithm draws between two microphones is:

Step 201: input signal x (n) is converted vectorial s (n) by orthogonal transform matrix, i.e. s (n)=T _{dCT (i, j)}x (n); Described transformation matrix is:

Wherein, i is the line number of transformation matrix; J is the columns of transformation matrix; N is the number of sampled point;

Step 202: adopt the public iteration of the LMS algorithm improved to obtain wave filter weight coefficient vector ω (n); Detailed process is:

Step a: the error amount e (0) of given initial filter weight coefficient vector ω (1), initial time and initial self-adaptative adjustment step-length σ (1);

Step b: obtain wave filter weight coefficient ω (n) according to formula (4) and (5) iteration;

e(n)=d(n)-s(n)ω ^T(n)（4）

ω(n+1)=ω(n)+σ(n)e(n)s(n)（5）

Wherein, $\mathrm{\&sigma;}(n+1)=(1-\mathrm{\&lambda;})\mathrm{\&sigma;}\left(n\right)+\mathrm{\&lambda;}{[e\left(n\right)e(n-1)+\underset{i=0}{\overset{n-1}{\mathrm{\&Sigma;}}}\mathrm{\&epsiv;}\left(k\right)e^2(n-k)]}^2;$ N is the number of sampled point, the error amount in e (n) moment for this reason; D (n) is desired value, i.e. desired output; S (n) is the input vector after discrete cosine transform, ω (n) is wave filter weight coefficient vector, σ (n) is self-adaptative adjustment step-length, λ determines the influence degree of step-length by transient error power, the imbalance of 0< λ <1 control algolithm and speed of convergence; ε (k) is for forgeing weighting factor, and the expression formula of ε (i) is: k=0,1,2 ..., n-1; control the rate of decay of weighting factor;

Step c: whether error in judgement value e (n) is less than or equal to the error amount of setting, if do not met, then continues to perform step b; If met, then output filter weight coefficient ω (n);

Step 203: travel-time τ wave filter weight coefficient ω (n) being tried to achieve to sound wave by peakvalue's checking.

The computing formula of described acoustic wave propagation velocity c is:

$c=\frac{L}{\mathrm{\&tau;}}$

Wherein, L is measuring point distance, unit: rice; τ is acoustic transit time.

Beneficial effect of the present invention is: the change utilizing sound wave velocity of propagation in soft air, calculate the height of the indoor velocity of sound, record indoor temperature and pressure by temperature sensor and pressure transducer simultaneously, then by calculating the calculating formula of indoor relative humidity, draw indoor relative humidity, real time on-line monitoring, the average relative humidity that true reflection is indoor, reduces operation cost.

Accompanying drawing explanation

Fig. 1 is indoor relative humidity on-line monitoring system schematic diagram provided by the invention;

Fig. 2 is indoor relative humidity on-line monitoring system installation site figure provided by the invention;

Fig. 3 is indoor relative humidity on-line monitoring system time delay algorithm process flow diagram provided by the invention;

Fig. 4 is indoor relative humidity on-line monitoring system operational flow diagram provided by the invention;

Fig. 5 is indoor relative humidity on-line monitoring system fundamental diagram;

Fig. 6 is indoor relative humidity on-line monitoring system fundamental diagram;

Wherein, the tested indoor of 1-; 2-dynamic loudspeaker; 3-microphone; 4-temperature sensor; 5-pressure transducer; 6-main control computer; 7-operating personnel; 8-first acoustic measurement device; 9-second acoustic measurement device.

Embodiment

Below in conjunction with accompanying drawing, preferred embodiment is elaborated.It should be emphasized that following explanation is only exemplary, instead of in order to limit the scope of the invention and apply.

Fig. 1 is indoor relative humidity on-line monitoring system schematic diagram provided by the invention.In Fig. 1, described system comprises two acoustic measurement devices, signal conditioner, power amplifier, data collecting card, sound card and main control computers; Described acoustic measurement device comprises dynamic loudspeaker 2, microphone 3, temperature sensor 4, pressure transducer 5 and terminal box; Described power amplifier, microphone 3, temperature sensor 4 are connected with the input end of terminal box respectively with pressure transducer 5; The output terminal of described terminal box is connected with described signal conditioner and dynamic loudspeaker 2 respectively; Described signal conditioner, data collecting card are connected in turn with main control computer 6; Described power amplifier, sound card are connected in turn with main control computer 6;

Wherein, described dynamic loudspeaker 2 is for signal of sounding; Described microphone 3 is for being converted to voltage signal by acoustical signal; Described temperature sensor 4 is for detecting indoor temperature; Described pressure transducer 5 is for detecting room pressure; Described signal conditioner is used for carrying out filtering and amplification to the received signal; Described data collecting card is used for collection signal, and the signal collected is sent to main control computer 6; The sound that described power amplifier is used for sound card produces amplifies.

Fig. 2 is indoor relative humidity on-line monitoring system installation site figure provided by the invention.In Fig. 2, described two acoustic measurement devices are installed on the relative position on the indoor same cross section 1-1 of body of wall relatively; One of them acoustic measurement device is as flexible piezoelectric sound-generating devices, and another acoustic measurement device is as sound receiver.

Fig. 3 is indoor relative humidity on-line monitoring system time delay algorithm process flow diagram provided by the invention.In Fig. 3, the process of the acoustic transit time τ that described employing time delay algorithm draws between two microphones is:

Step 301: input signal x (n) is converted vectorial s (n) by orthogonal transform matrix, i.e. s (n)=T _{dCT (i, j)}x (n); Described transformation matrix is:

Wherein, i is the line number of transformation matrix; J is the columns of transformation matrix; N is the number of sampled point;

Step 302: adopt the public iteration of the LMS algorithm improved to obtain wave filter weight coefficient vector ω (n); Detailed process is:

Step a: the error amount e (0) of given initial filter weight coefficient vector ω (1), initial time and initial self-adaptative adjustment step-length σ (1);

Step b: obtain wave filter weight coefficient ω (n) according to formula (4) and (5) iteration;

e(n)=d(n)-s(n)ω ^T(n)（4）

ω(n+1)=ω(n)+σ(n)e(n)s(n)（5）

Wherein, $\mathrm{\&sigma;}(n+1)=(1-\mathrm{\&lambda;})\mathrm{\&sigma;}\left(n\right)+\mathrm{\&lambda;}{[e\left(n\right)e(n-1)+\underset{i=0}{\overset{n-1}{\mathrm{\&Sigma;}}}\mathrm{\&epsiv;}\left(k\right)e^2(n-k)]}^2;$ N is the number of sampled point, the error amount in e (n) moment for this reason; D (n) is desired value, i.e. desired output; S (n) is the input vector after discrete cosine transform, ω (n) is wave filter weight coefficient vector, σ (n) is self-adaptative adjustment step-length, λ determines the influence degree of step-length by transient error power, the imbalance of 0< λ <1 control algolithm and speed of convergence; ε (k) is for forgeing weighting factor, and the expression formula of ε (i) is: k=0,1,2 ..., n-1; control the rate of decay of weighting factor;

Step c: whether error in judgement value e (n) is less than or equal to the error amount of setting, if do not met, then continues to perform step b; If met, then output filter weight coefficient ω (n);

Step 303: travel-time τ wave filter weight coefficient ω (n) being tried to achieve to sound wave by peakvalue's checking.

Fig. 4 is indoor relative humidity on-line monitoring system operational flow diagram provided by the invention.In Fig. 4, during described system works, main control computer controls sound card and produces voice signal, and by power amplifier, voice signal is amplified, then send dynamic loudspeaker to sound, detected by the microphone of the same side, then sound wave to be received by the microphone of offside body of wall to relative body of wall through indoor propagation; Acoustical signal is converted to voltage signal by the microphone of offside body of wall, and by signal conditioner filtering and amplification, data collecting card collects these signals through the input end of terminal box; The temperature sensor and the pressure transducer that are positioned at below can record indoor temperature and pressure simultaneously, and the input end through terminal box is obtained by data collecting card; The signal of acquisition is analyzed by main control computer, draws the acoustic transit time between two microphones by time delay algorithm.Because the distance between two microphones is fixed and known, calculate the velocity of propagation of sound wave between two microphones.Pressure transducer can record indoor pressure simultaneously, and temperature sensor can record indoor temperature, according to the pressure P recorded and temperature T, can draw indoor atmospheric density ρ by the software in main control computer ₁, water vapour density p ₂and pressure P _s, the air of indoor, the density of water vapor and force value are substituted in the expression formula of A, B, C, thus draw A, B, C tri-parameters in computing formula, and then calculate relative humidity and show at main control computer display window.

Fig. 5 and Fig. 6 is indoor relative humidity on-line monitoring system fundamental diagram.In Fig. 5, voice signal sends by being positioned at the first acoustic measurement device 8 that installation cross section is arranged, the second acoustic measurement device 9 being disposed in relative body of wall measures.By the measurement of acoustic transit time, can be used for determining the average velocity of sound wave on travel path.In Fig. 6, voice signal sends by being positioned at the second acoustic measurement device 9 that installation cross section is arranged, the first acoustic measurement device 8 being disposed in relative body of wall measures.In order to improve precision, weighted mean value is got to the result of twice measurement in Fig. 5 and Fig. 6.

The above; be only the present invention's preferably embodiment, but protection scope of the present invention is not limited thereto, is anyly familiar with those skilled in the art in the technical scope that the present invention discloses; the change that can expect easily or replacement, all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection domain of claim.

Claims (4)

1. indoor relative humidity computing method, is characterized in that, described method specifically comprises the following steps:

Step 1: according to water capacity formula gentle/liquid two-phase in the expression formula of the velocity of sound $c=c_1{\left\{\frac{[\mathrm{\&alpha;}{\mathrm{\&rho;}}_1+(1-\mathrm{\&alpha;}+C_R){\mathrm{\&rho;}}_2]{\mathrm{\&rho;}}_1}{(1-\mathrm{\&alpha;}){\mathrm{\&rho;}}_2(1+C_R-\mathrm{\&alpha;}{C}_R){\mathrm{\&rho;}}_1+\mathrm{\&alpha;}{C}_R{\mathrm{\&rho;}}_2}\right\}}^{\frac{1}{2}},$ Wherein, c is sound velocity of wave propagation in medium, unit: meter per second; ρ ₁for the density of air, unit: kilograms per cubic meter; ρ ₂for the density of water vapor, kilograms per cubic meter; C _rfor mass coefficient; P _sfor equality of temperature is with steam-laden partial pressure in the saturated wet steam of pressure, unit: Pascal; P is the pressure that pressure transducer records; T is the temperature that temperature sensor records, unit: degree Celsius; for indoor relative humidity; wherein γ is the adiabatic exponent of gas; R is gas molar quality; Obtain the computing formula of indoor relative humidity;

Step 2: employing time delay algorithm draws the acoustic transit time τ between two microphones;

Step 3: because the distance between two microphones is fixed and known, calculate the acoustic wave propagation velocity c of sound wave between two microphones;

Step 4: the acoustic wave propagation velocity c that step 3 is obtained, the temperature T that the pressure P recorded according to pressure transducer and temperature sensor record, and by drawing indoor atmospheric density ρ in main control computer ₁, water vapour density p ₂and pressure P _ssubstitute in the coefficient expressions of the computing formula of indoor relative humidity, thus draw design factor A, B and the C in indoor relative humidity formula, and then go out indoor relative humidity by indoor relative humidity formulae discovery.

2. method according to claim 1, is characterized in that, the computing formula of described indoor relative humidity:

Wherein, coefficient A, B, C is the design factor of relative humidity; The expression formula of coefficient is:

$\begin{array}{c}A=155500P_s^2{\mathrm{\&rho;}}_{1}c({\mathrm{\&rho;}}_1{\mathrm{\&rho;}}_2{c}^2+{\mathrm{\&rho;}}_2{C}_R{c}^2-{\mathrm{\&rho;}}_1^2{c}_1^2-{\mathrm{\&rho;}}_1{\mathrm{\&rho;}}_2{c}_1^2-2{\mathrm{\&rho;}}_1{\mathrm{\&rho;}}_2{C}_R{c}_1^2)\\ -25000{\mathrm{\&rho;}}_1^3{\mathrm{\&rho;}}_2{P}_s^2(c^2+c^2{C}_R-c_1^2-C_R{c}_1^2)\\ +96721P_s^2{c}^2(-{\mathrm{\&rho;}}_2{C}_R{c}^2+{\mathrm{\&rho;}}_1^2{c}_1^2+{\mathrm{\&rho;}}_1{\mathrm{\&rho;}}_2{C}_R{c}_1^2)\end{array};$

$\begin{array}{c}B=50000{\mathrm{\&rho;}}_1^3{\mathrm{\&rho;}}_2{P}_{s}P(c+C_R{c}^2-c_1^2-C_R{c}_1^2)+155500{\mathrm{\&rho;}}_1{P}_s\mathrm{Pc}(-{\mathrm{\&rho;}}_1{\mathrm{\&rho;}}_2{c}^2\\ -{\mathrm{\&rho;}}_2{C}_R{c}^2+{\mathrm{\&rho;}}_1^2{c}_1^2+2{\mathrm{\&rho;}}_1{\mathrm{\&rho;}}_2{C}_R{c}_1^2\end{array};$

$C=250000{\mathrm{\&rho;}}_1^3{\mathrm{\&rho;}}_2{P}^2(c_1^2-C_R{c}^2-{\mathrm{\&rho;}}_1{c}^2+{\mathrm{\&rho;}}_1{C}_R{c}_1^2);$

Wherein, c is sound velocity of wave propagation in medium, unit: meter per second; ρ ₁for the density of air, unit: kilograms per cubic meter; ρ ₂for the density of water vapor, kilograms per cubic meter; C _rfor mass coefficient; P _sfor equality of temperature is with steam-laden partial pressure in the saturated wet steam of pressure, unit: Pascal; P is the pressure that pressure transducer records; T is the temperature recorded by temperature sensor, unit: degree Celsius; for indoor relative humidity; wherein γ is the adiabatic exponent of gas; R is gas molar quality.

3. method according to claim 1, is characterized in that, the process of the acoustic transit time τ that described employing time delay algorithm draws between two microphones is:

Step 201: input signal x (n) is converted vectorial s (n) by orthogonal transform matrix, i.e. s (n)=T _{dCT (i, j)}x (n); Described transformation matrix is:

Wherein, i is the line number of transformation matrix; J is the columns of transformation matrix; N is the number of sampled point;

Step 202: adopt the public iteration of the LMS algorithm improved to obtain wave filter weight coefficient vector ω (n); Detailed process is:

Step a: the error amount e (0) of given initial filter weight coefficient vector ω (1), initial time and initial self-adaptative adjustment step-length σ (1);

Step b: obtain wave filter weight coefficient ω (n) according to formula (4) and (5) iteration;

e(n)＝d(n)-s(n)ω ^T(n)(4)

ω(n+1)＝ω(n)+σ(n)e(n)s(n)(5)

Wherein, $\mathrm{\&sigma;}(n+1)=(1-\mathrm{\&lambda;})\mathrm{\&sigma;}\left(n\right)+\mathrm{\&lambda;}{[e\left(n\right)e(n-1)+\underset{k=0}{\overset{n-1}{\mathrm{\&Sigma;}}}\mathrm{\&epsiv;}\left(k\right)e^2(n-k)]}^2;$ N is the number of sampled point, the error amount in e (n) moment for this reason; D (n) is desired value, i.e. desired output; S (n) is the input vector after discrete cosine transform, ω (n) is wave filter weight coefficient vector, σ (n) is self-adaptative adjustment step-length, λ determines the influence degree of step-length by transient error power, the imbalance of 0< λ <1 control algolithm and speed of convergence; ε (k) is for forgeing weighting factor, and the expression formula of ε (k) is: k=0,1,2 ..., n-1; control the rate of decay of weighting factor; T representing matrix transposition;

Step c: whether error in judgement value e (n) is less than or equal to the error amount of setting, if do not met, then continues to perform step b; If met, then output filter weight coefficient ω (n);

Step 203: travel-time τ wave filter weight coefficient ω (n) being tried to achieve to sound wave by peakvalue's checking.

4. method according to claim 1, is characterized in that, the computing formula of described acoustic wave propagation velocity c is:

$c=\frac{L}{\mathrm{\&tau;}}$

Wherein, L is measuring point distance, unit: rice; τ is acoustic transit time, unit: second.